否则，条款将无法正常工作，这是怎么了? [英] otherwise-clause not working as expect , whats wrong here?

问题描述

我正在使用spark-sql-2.4.1v如何执行各种联接，具体取决于列的值，我需要获取给定值列的map_val列的多个查找值，如下所示.

I am using spark-sql-2.4.1v how to do various joins depend on the value of column I need get multiple look up values of map_val column for given value columns as show below.

样本数据:

val data = List(
  ("20", "score", "school", "2018-03-31", 14 , 12),
  ("21", "score", "school", "2018-03-31", 13 , 13),
  ("22", "rate", "school", "2018-03-31", 11 , 14),
  ("21", "rate", "school", "2018-03-31", 13 , 12)
 )
val df = data.toDF("id", "code", "entity", "date", "value1", "value2")

df.show

+---+-----+------+----------+------+------+
| id| code|entity|      date|value1|value2|
+---+-----+------+----------+------+------+
| 20|score|school|2018-03-31|    14|    12|
| 21|score|school|2018-03-31|    13|    13|
| 22| rate|school|2018-03-31|    11|    14|
| 21| rate|school|2018-03-31|    13|    12|
+---+-----+------+----------+------+------+




 val resultDs = df
                 .withColumn("value1",
                        when(col("code").isin("rate") , functions.callUDF("udfFunc",col("value1")))
                         .otherwise(col("value1").cast(DoubleType))
                      )

udfFunc映射如下

11->a
12->b
13->c
14->d

预期输出

+---+-----+------+----------+------+------+
| id| code|entity|      date|value1|value2|
+---+-----+------+----------+------+------+
| 20|score|school|2018-03-31|    14|    12|
| 21|score|school|2018-03-31|    13|    13|
| 22| rate|school|2018-03-31|    a |    14|
| 21| rate|school|2018-03-31|    c |    12|
+---+-----+------+----------+------+------+

但它的输出为

+---+-----+------+----------+------+------+
| id| code|entity|      date|value1|value2|
+---+-----+------+----------+------+------+
| 20|score|school|2018-03-31|  null|    12|
| 21|score|school|2018-03-31|  null|    13|
| 22| rate|school|2018-03-31|    a |    14|
| 21| rate|school|2018-03-31|    c |    12|
+---+-----+------+----------+------+------+

为什么要否则"?条件无法正常工作.知道这里有什么问题吗??

why "otherwise" condition is not working as expected. any idea what is wrong here ??

推荐答案

列应包含相同的数据类型.

Column should contains same datatype.

注意-DoubleType无法存储StringTyp数据，因此您需要将DoubleType转换为StringType.

Note - DoubleType can not store StringTyp data, So you need to convert DoubleType to StringType.

val resultDs = df
.withColumn("value1",
        when(col("code") === lit("rate") ,functions.callUDF("udfFunc",col("value1")))
        .otherwise(col("value1").cast(StringType)) // Should be StringType
    )

或

val resultDs = df
                 .withColumn("value1",
                        when(col("code").isin("rate") , functions.callUDF("udfFunc",col("value1")))
                         .otherwise(col("value1").cast(StringType)) // Modified to StringType
                      )

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